A new perturbative approach to the adiabatic approximation

A new and intuitive perturbative approach to time-dependent quantum mechanics problems is presented, which is useful in situations where the evolution of the Hamiltonian is slow. The state of a system which starts in an instantaneous eigenstate of the initial Hamiltonian is written as a power series which has a straightforward diagrammatic representation. Each term of the series corresponds to a sequence of "adiabatic" evolutions, during which the system remains in an instantaneous eigenstate of the Hamiltonian, punctuated by transitions from one state to another. The first term of this series is the standard adiabatic evolution, the next is the well-known first correction to it, and subsequent terms can be written down essentially by inspection. Although the final result is perhaps not terribly surprising, it seems to be not widely known, and the interpretation is new, as far as we know. Application of the method to the adiabatic approximation is given, and some discussion of the validity of this approximation is presented.Comment: 9 pages. Added references, discussion of previous results, expanded upon discussion of main result and application of i

Prevalence and Patterns of Major Depressive Disorder in the United States Labor Force

Background and Aims of the Study: In this paper, we identify the 12-month and lifetime prevalence of major depressive disorder in and out of the labor force, and among the employed and unemployed. We examine whether prevalence by labor force and employment status varies by gender and over the life cycle. Finally, we examine whether people can ‘recover’ from depression with time by identifying patterns of labor force participation and employment as time since most recent episode passes. Methods: We examine data collected as part of the National Comorbidity Survey, a survey representative of the population of the United States designed to identify the prevalence of major mental illnesses. The National Comorbidity Study identified cases of major depression via the Composite International Diagnostic Interview. Using these data, we estimate univariate and bivariate frequency distributions of major depressive disorder. We also estimate a set of multivariate models to identify the effect of a variety of dimensions of major depression on the propensity to participate in the labor force, and be employed if participating. Results: Lifetime and 12-month prevalence rates of depression are similar in and out of the labor force. Within the labor force, however, depression is strongly associated with unemployment. The negative relationship between depressive disorder and employment is particularly strong for middle age workers. Depression and the number of depressive episodes have a differing pattern of effects on labor market outcomes for men and women. We find evidence that labor force participation and employment rates for people with a history of depression increase significantly over time in the absence of additional depressive episodes. Discussion: Labor market status represents an important dimension along which prevalence of major depression varies. The relationship between depression and employment status is particularly strong for middle aged persons, but becomes weaker as time passes since the last depressive episode. Continued exploration of the association between work (or lack of work) and depression may ultimately help in the prediction, treatment and assessment of the illness. Implications for Practice and Policy: These results present a basic set of facts about the relationship between major depressive disorder and labor market outcomes. We have not, however, attempted to sort out the complexities of this relationship here. These complexities arise at almost every turn. For instance, the high level of prevalence of depression among the unemployed may be due to the possibility that the stresses associated with unemployment trigger depressive episodes or to the possibility that workers who are depressed are more likely to be fired or quit. Implications for Further Research: Our continuing research attempts to address these problems. Understanding when and how depression affects labor market outcomes and when and how labor market outcomes affect depression is an important endeavor for those interested in treating the disease and understanding its consequences.Funded by National Institute of Mental Health. Grant Number: R01-MH56463-0

Modulation of en-route charges to redistribute traffic in the European airspace

Peak-load pricing (PLP), a two-tariffs charging scheme commonly used in public transport and utilities, is tested on the European Air Traffic Management (ATM) system as a means for reducing capacity-demand imbalances. In particular, a centralised approach to PLP (CPLP) where a Central Planner (CP) sets en-route charges on the network is presented. CPLP consists of two phases: in the first, congested airspace sectors and their peak and off-peak hours are identified; in the second, CP assesses and sets en-route charges in order to reduce overall shift on the network. Such charges should guarantee that Air Navigation Service Providers (ANSPs) are able to recover their operational costs while inducing the Airspace Users (AUs) to route their flights in a way that respects airspace capacity. The interaction between CP and AUs is modelled as a Stackelberg game and formulated by means of bilevel linear programming. Two heuristic approaches, based on Coordinate-wise Descent and Genetic Algorithms are implemented to solve the CPLP model on a data set obtained from historical data for an entire day of traffic on European airspace. Results show that significant improvements in traffic distribution in terms of shift and sector load can be achieved through this simple en-route charges modulation scheme

Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked: 1. Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements. 2. What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways. We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)

NcPred for accurate nuclear protein prediction using n-mer statistics with various classification algorithms

Prediction of nuclear proteins is one of the major challenges in genome annotation. A method, NcPred is described, for predicting nuclear proteins with higher accuracy exploiting n-mer statistics with different classification algorithms namely Alternating Decision (AD) Tree, Best First (BF) Tree, Random Tree and Adaptive (Ada) Boost. On BaCello dataset [1], NcPred improves about 20% accuracy with Random Tree and about 10% sensitivity with Ada Boost for Animal proteins compared to existing techniques. It also increases the accuracy of Fungal protein prediction by 20% and recall by 4% with AD Tree. In case of Human protein, the accuracy is improved by about 25% and sensitivity about 10% with BF Tree. Performance analysis of NcPred clearly demonstrates its suitability over the contemporary in-silico nuclear protein classification research

SATURN D6.5 - Final Report

The objective of the SATURN (Strategic Allocation of Traffic Using Redistribution in the Network) project is to make novel and credible use of market-based demand-management mechanisms to redistribute air traffic in the European airspace. This reduces congestion and saves the airspace users operational costs. The project is motivated by frequent demand and capacity imbalances in the European airspace network, which are forecast to continue in the near future. The present and foreseen ways of dealing with such imbalances mainly concern strategic and tactical capacity-side interventions, such as resectorisation and opening of more sectors to deal with excess demand. These are followed by tactical demand management measures, if needed. As a result, not only do substantial costs arise, but airspace users are also typically left with no choice but to comply with imposed air traffic flow management measures. The project shows how economic signals could be given to airspace users and air navigation service providers (ANSPs) to improve capacity-demand balancing, airspace design and usage, and what the benefits would be of a centralised planner compared with those of decentralised maximisation of self interests (by the ANSPs and/or airspace users)

Validation of a liquid chromatography-tandem mass spectrometry method for analyzing cannabinoids in oral fluid.

A liquid chromatography tandem mass spectrometry method was developed for quantifying ten cannabinoids in oral fluid (OF). This method utilizes OF collected by the Quantisal™ device and concurrently quantifies cannabinol (CBN), cannabidiol (CBD), Δ9-tetrahydrocannabinol (THC), 11-hydroxy-Δ9-THC (11-OH-THC), 11-nor-9-carboxy-Δ9-THC (THC-COOH), 11-nor-9-carboxy-Δ9-THC glucuronide (THC-COOH-gluc), Δ9-THC glucuronide (THC-gluc), cannabigerol (CBG), tetrahydrocannabiverin (THCV), and Δ9-tetrahydrocannabinolic acid A (THCA-A). Solid phase extraction was optimized using Oasis Prime HLB 30 mg 96-well plates. Cannabinoids were separated by liquid chromatography over a BEH C18 column and detected by a Waters TQ-S micro tandem mass spectrometer. The lower limits of quantification (LLOQ) were 0.4 ng/mL for CBN, CBD, THC, 11-OH-THC, THC-gluc, and THCV; and 1.0 ng/mL for THC-COOH, THC-COOH-gluc, CBG and THCA-A. Linear ranges extended to 2000 ng/mL for THC and 200 ng/mL for all other analytes. Inter-day analytical bias and imprecision at three levels of quality control (QC) was within ±15%. Mean extraction efficiencies ranged from 26.0-98.8%. Applicability of this method was tested using samples collected from individuals randomly assigned to smoke either a joint containing <0.1%, 5.9%, or 13.4% THC content. This method was able to identify and calculate the concentration of 6 of 10 cannabinoids validated in this method

Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms

We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links, known as Pigou's network. We improve upon the value 4/3 by means of Coordination Mechanisms. We increase the latency functions of the edges in the network, i.e., if $\ell_e(x)$ is the latency function of an edge $e$, we replace it by $\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an adversary fixes a demand rate as input. The engineered Price of Anarchy of the mechanism is defined as the worst-case ratio of the Nash social cost in the modified network over the optimal social cost in the original network. Formally, if \CM(r) denotes the cost of the worst Nash flow in the modified network for rate $r$ and \Copt(r) denotes the cost of the optimal flow in the original network for the same rate then [\ePoA = \max_{r \ge 0} \frac{\CM(r)}{\Copt(r)}.] We first exhibit a simple coordination mechanism that achieves for any network of parallel links an engineered Price of Anarchy strictly less than 4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25. Then, for the case of two parallel links, we describe an optimal mechanism; its engineered Price of Anarchy lies between 1.191 and 1.192.Comment: 17 pages, 2 figures, preliminary version appeared at ESA 201

Outcomes Following Discectomy for Far Lateral Disc Herniation Are Not Predicted by Obstructive Sleep Apnea

Introduction: Previous studies have demonstrated that obstructive sleep apnea (OSA) is associated with adverse postoperative outcomes, but few studies have examined OSA in a purely spine surgery population. This study investigates the association of the STOP-Bang questionnaire, a screening tool for undiagnosed OSA, with adverse events following discectomy for far lateral disc herniation (FLDH). Methods: All adult patients (n = 144) who underwent FLDH surgery at a single, multihospital, academic medical center (2013-2020) were retrospectively enrolled. Univariate logistic regression was performed to evaluate the relationship between risk of OSA (low- or high-risk) according to STOP-Bang score and postsurgical outcomes, including unplanned hospital readmissions, ED visits, and reoperations. Results: Ninety-two patients underwent open FLDH surgery, while 52 underwent endoscopic procedures. High risk of OSA according to STOP-Bang score did not predict risk of readmission, ED visit, outpatient office visit, or reoperation of any kind within either 30 days or 30-90 days of surgery. High risk of OSA also did not predict risk of reoperation of any kind or repeat neurosurgical intervention within 30 days or 90 days of the index admission (either during the same admission or after discharge). Conclusion: The STOP-Bang questionnaire is not a reliable tool for predicting post-operative morbidity and mortality for FLDH patients undergoing discectomy. Additional studies are needed to assess the impact of OSA on morbidity and mortality in other spine surgery populations